RQGIS 0.1.0 release

We proudly announce the release of RQGIS! RQGIS establishes an interface between R and QGIS, i.e. it allows the user to access the more than 1000 QGIS geoalgorithms from within R. To install it, run:

install.packages("RQGIS")

Naturally, you need to install other software (such as QGIS) to run RQGIS properly. Therefore, we wrote a package vignette, which guides you through the installation process of QGIS, GRASS and SAGA on various platforms. To access it, run:

vignette("install_guide", package = "RQGIS")

How to use RQGIS

To introduce RQGIS, we will demonstrate how to calculate the SAGA topographic wetness index. The first step is the creation of a QGIS environment. This is a list containing the paths RQGIS needs to access QGIS. Luckily for us, set_env does this for us. We merely need to specify the root path to the QGIS installation. This is most likely something like C:/OSGeo4W~1 on Windows, /usr on Linux and /usr/local/Cellar on a Mac. If we do not specify a path to the QGIS root folder, set_env tries to figure it out. This, however, might be time-consuming depending on the size of the drives to search.

library("RQGIS")
env <- set_env()

Secondly, we need to find out the name of the function in QGIS which calculates the wetness index:

find_algorithms("wetness index", name_only = TRUE, qgis_env = env)

## [1] "taudem:topographicwetnessindex"  "saga:sagawetnessindex"          
## [3] "saga:topographicwetnessindextwi" ""

There are three algorithms containing the words wetness and index in their short description. Here, we choose saga:sagawetnessindex. To retrieve the corresponding function arguments, we use get_args_man. By setting option to TRUE, we indicate that we would like to use the default values, if available:

args <- get_args_man(alg = "saga:sagawetnessindex", 
                     options = TRUE,
                     qgis_env = env)
# print the retrieved list
args

## $DEM
## [1] "None"
## 
## $SUCTION
## [1] "10.0"
## 
## $AREA_TYPE
## [1] "0"
## 
## $SLOPE_TYPE
## [1] "0"
## 
## $SLOPE_MIN
## [1] "0.0"
## 
## $SLOPE_OFF
## [1] "0.1"
## 
## $SLOPE_WEIGHT
## [1] "1.0"
## 
## $AREA
## [1] "None"
## 
## $SLOPE
## [1] "None"
## 
## $AREA_MOD
## [1] "None"
## 
## $TWI
## [1] "None"

Of course, we need to specify certain function arguments such as the input (DEM) and output (TWI) arguments. Please note that RQGIS accepts as input argument either the path to a spatial object or a spatial object residing in R. Here, we will use a digital elevation model, which comes with the RQGIS package:

# load data into R
data("dem", package = "RQGIS")
# define input
args$DEM <- dem
# specify output path
args$TWI <- "twi.sdat"

Finally, we can access QGIS from within R by supplying run_qgis with the specified arguments as a list. Specifying also the load_output-argument directly loads the QGIS output into R.

twi <- run_qgis(alg = "saga:sagawetnessindex", 
                params = args, 
                load_output = args$TWI, 
                qgis_env = env)

# visualize the result
library("raster")
hs <- hillShade(terrain(dem), terrain(dem, "aspect"), 40, 270)
pal <- RColorBrewer::brewer.pal(6, "Blues")
spplot(twi, col.regions = pal, alpha.regions = 0.8,
       scales = list(tck = c(1, 0)),               
       colorkey = list(space = "bottom",
                               width = 1, height = 0.5,
                       axis.line = list(col = "black")),
       cuts = length(pal) - 1) +
  latticeExtra::as.layer(spplot(hs, col.regions = gray(0:100 / 100)), 
                         under = TRUE)

 

For more information on RQGIS, please refer to https://github.com/jannes-m/RQGIS.